Creating Context Packs for AI
Quick start
Collect or infer:
- •Feature name and scope
- •Existing context documents (state maps, vocabulary, content briefs)
- •AI system requirements (token limits, format constraints)
- •Content types the AI will generate
- •Guardrails and constraints the AI must respect
Then produce output using TEMPLATES.md. Validate with RUBRIC.md.
Workflow
- •Gather all existing feature context (vocabulary, states, constraints, tone).
- •Identify what content the AI will generate and in what contexts.
- •Structure context following the context pack schema.
- •Include explicit constraints and prohibited patterns.
- •Add examples of correct and incorrect outputs.
- •Validate completeness using the completeness checklist.
- •Test with target AI system to verify usability.
- •Run the rubric check. Revise until it passes.
Degrees of freedom
- •Default: Low. Context packs must be precise and complete.
- •Allowed variation: Format may adapt to AI system requirements. Detail level may vary by content complexity.
Failure modes to avoid
- •Omitting constraints that lead to off-brand content
- •Including redundant information that wastes tokens
- •Using ambiguous language that AI interprets differently than intended
- •Missing state-specific guidance (AI doesn't know what state it's writing for)
- •Providing examples without explaining why they're correct
- •Creating context packs that exceed AI token limits
References
- •Templates: TEMPLATES.md
- •Rubric: RUBRIC.md
- •Examples: EXAMPLES.md
- •Context pack schema: reference/context-pack-schema.md
- •Completeness checklist: reference/completeness-checklist.md